Alternatives Assessment 123 Webinar: Mechanistic Data in a Systematic Review Framework: Developing Confidence in Bodies of Evidence JANUARY 21, 2015 FACILITATED BY: JOEL TICKNER, SCD JOEL_TICKNER@UML.EDU LOWELL CENTER FOR SUSTAINABLE PRODUCTION, UMASS LOWELL * If you would like to ask a question or comment during this webinar please type your question in the Q&A box located in the control panel.
Goals Continuing education and dialog To advance the practice of alternatives assessment for informed substitution across federal, state, and local agencies through networking, sharing of experiences, development of common approaches, tools, datasets and frameworks, and creation of a community of practice.
Purpose of this call • Alternatives assessment processes often suffer from significant gaps in toxicological data • High throughput in-vitro screens provide a means to fill data gaps and serve as primary data • The objective of the Tox 21 partnership, a multi-agency collaborative effort, is to shift the assessment of chemical hazards from traditional experimental animal toxicology studies to one based on target-specific, mechanism- based, biological observations largely obtained using in vitro assays, with the ultimate aim of improving risk assessment for humans and the environment and the design of safer chemicals • A key goal is to develop better predictive tools
To view program and to register visit: www.saferalternatives.org
Speaker Dr. Andrew Rooney Office of Health Assessment and Translation, National Institute of Environmental Health Sciences
Discussion Questions • What are the strengths and weaknesses of high throughput screening data for both data gap filling and as primary data to support alternatives assessment? • How useful/usable is Tox 21 data for both comparing chemical alternatives and designing safer molecules at the present time. • What are the challenges and opportunities to more effective integration of these data streams in chemical alternatives assessment?
Webinar Discussion Instructions Due to the number of participants on the Webinar, all lines will be muted. If you wish to ask a question, please type your question in the Q&A box located in the drop down control panel at the top of the screen. All questions will be answered at the end of the presentations.
Mechanistic Data in a Systematic Review Framework: Developing Confidence in Bodies of Evidence Andrew Rooney, PhD Office of Health Assessment and Translation National Institute of Environmental Health Sciences January 21, 2015
Presentation Outline • Background – Office of Health Assessment and Translation – Systematic review, mechanistic data, and environmental health questions • Mechanistic Data in the OHAT Framework – Planning – Identifying the evidence – Evaluating the evidence – Integrating the evidence • Challenges and Ongoing Methods Development • Questions – SR on OHAT Website (http://ntp.niehs.nih.gov/go/38673)
Office of Health Assessment and Translation • Conduct literature-based evaluations OHAT Evaluations to assess the evidence that environmental substances cause adverse health effects – Hazard or State-of-science evaluations – Provide opinions on whether substances may be of concern given current human exposure NTP National Toxicology Program U.S. Department of Health and Human Services NTP Monograph • Methods development Developmental Effects and Pregnancy Outcomes Associated With Cancer Chemotherapy Use During Pregnancy – Systematic review – Increasing integration of mechanistic data – Approaches to assess confidence in mechanistic data Month 2013
Systematic Review Requirements for Environmental Health • Address breadth of relevant data – Wide range of human study designs – Animal studies Human studies – Mechanistic studies ( in vitro and other relevant data) • Procedure to integrate evidence streams Animal studies • Dual role for mechanistic data – 1) Integrate with human/animal evidence – 2) Potential to support decisions in absence of human or animal data Mechanistic studies Alternatives often have small, primarily mechanistic data sets
OHAT Framework Extends Existing Systematic Review Methods • Evidence Integration – The process for reaching conclusions on the NTP’s confidence across a body of studies within an evidence stream (i.e., human and animal data separately) and then integrating those conclusions across the evidence streams with consideration of other relevant data such as supporting evidence from mechanistic studies – Lack of consensus on term “Weight of Evidence”? (Weed et al., 2005) Systematic Review Evidence Integration Problem Search for Assess Rate Translate Extract Integrate Evidence Formulation and Select Quality of Confidence Confidence into Data from to Develop Hazard and Prepare Studies for Individual in Body of Level of Evidence Studies ID Conclusions Protocol Inclusion Studies Evidence for Health Effects
OHAT Framework Systematic Review and Evidence Integration Increased transparency and objectivity • Applied to all three evidence streams (human, animal, mechanistic) • Framework for documenting the basis of scientific judgments − Individual study quality − Confidence in bodies of evidence − Hazard ID conclusions • Procedures to integrate evidence streams Evidence Systematic Review Integration Develop Protocol Identify Evaluate Integrate Evidence Evidence Evidence Human Human Human Rate Confidence in Bodies Search for Studies Animal Animal Animal Of Evidence Assess Individual Select Studies Study Quality Develop Hazard Mechanistic Mechanistic Mechanistic Identification Extract Data Conclusions
Planning the Evaluation Planning step develops • Objectives Planning • Study question Scoping • PECO statement • Population • Exposures Broad Problem • Comparators Literature Formulation • Outcomes Search • Protocol Evidence Systematic Review Integration Develop Protocol Identify Evaluate Integrate Evidence Evidence Evidence Human Human Human Rate Confidence in Bodies Search for Studies Animal Animal Animal Of Evidence Assess Individual Select Studies Study Quality Develop Hazard Mechanistic Mechanistic Mechanistic Identification Extract Data Conclusions
PECO Statement Example: Evaluation of PFOA/PFOS immunotoxicity • PECOS for Human and non-human animal evidence – Population: Humans or animals without restriction on sex or life stage – Exposure: PFOA (CAS# 335-67-1) or PFOS (CAS# 1763-23-1) or their salts – Comparator: Humans or animals exposed to lower levels or vehicle – Outcomes: • Primary outcomes: Immune-related diseases and measures of immune function • Secondary outcomes: Immunostimulation and observational immune endpoints • What about Mechanistic evidence? – Outcomes: • Primary outcomes: Measures of immune function after in vitro exposure • Secondary outcomes: Observational immune endpoints after in vitro exposure
Consider Supplementing PECO Statement Mechanistic data should address relevant outcomes • How broadly should one collect mechanistic evidence? – For narrow, well-defined outcomes • PECO for mechanistic data developed in protocol • May require technical experts to ID mechanisms and list of search terms – For multiple outcomes or general health effects reviews • 1) Identify relevant mechanistic data if clearly known • 2) Plan to supplement with outcome-relevant mechanistic data – After health effects are identified, additional search may be warranted – All changes are documented Relevant outcomes may not be clear until after human and animal data are collected
Systematic Review Identifying the Evidence • Search for Studies Challenge for Mechanistic Data How narrowly do you define “relevant” studies? • Select Studies Or Which mechanistic data are relevant? • Extract Data Evidence Systematic Review Integration Develop Protocol Identify Evaluate Integrate Evidence Evidence Evidence Human Human Human Rate Confidence in Bodies Search for Studies Animal Animal Animal Of Evidence Assess Individual Select Studies Study Quality Develop Hazard Mechanistic Mechanistic Mechanistic Identification Extract Data Conclusions
Identify Evidence Selecting Studies: PFOA/PFOS Immunotoxicity Identification References identified References identified through through other sources database searches (n=4) (n=5,534) References after duplicate removal Title-abstract screened for References excluded for relevance and eligibility criteria established in protocol Screening (n=2,675) (n=2,364) # of full-text articles excluded for Full-text articles assessed for relevance and eligibility (n= 315) pre-established criteria, with reasons • Exposure not relevant (n=38) • Outcome not relevant (n=34) • Review (n=74) • Other (n=55) Studies included for data extraction in step 3, and • Not relevant:14 risk of bias assessment in step 4 (n=114) Included • Pharmacokinetic data only: 9 • Meeting Abstract Only: 26 • Grants: 6 Human studies Animal studies Mechanistic studies (n=19) (n=18) (n=80) n=3
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